Over the past decade, researchers have developed molecular technologies for disease diagnoses that analyze proteins and DNA/RNA messages that encode them. These developments have facilitated new insights into the causes of disease and into the early detection of diseases and the accompanying potential therapeutic response. Through genomics, scientists have determined that chromosomal and genetic abnormalities are fundamental sources of human disease. Chromosomal and genetic abnormalities encompass a broad range of irregularities, including numerical and structural changes in chromosomes, amplifications and deletions of genes, as well as mutations within specific gene sequences. Scientific evidence suggests that these chromosomal changes are integral to cancer progression and are the most significant markers of cancer detection. Molecular diagnostic laboratories have long used archaic, manual, and cumbersome techniques that often lead to poorly reproducible and inaccurate results. Even today, most molecular and cell-based diagnostic systems use outdated and non-integrated technologies unable to cost-effectively perform massively parallel-scale analyses. System capabilities are further stressed by the genomics revolution that has accelerated demand for potential markers for use in target validation in drug discovery and development. Consequently, additional automation and parallelism are sought to enable efficient specimen handling, processing and analysis.